U.S. International Equity Investment and Past and Prospective Returns**

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Abstract:

Counter to extant stylized facts, using newly available data on country allocations in U.S. investors' foreign equity portfolios we find that (i) U.S. investors do not exhibit returns-chasing behavior, but, consistent with partial portfolio rebalancing, tend to sell past winners; and (ii) U.S. investors increase portfolio weights on a country's equity market just prior to its strong performance, behavior inconsistent with an informational disadvantage. Over the past two decades, U.S. investors' foreign equity portfolios outperformed a value-weighted foreign benchmark by 160 basis points per year.

A wave of research in the 1990s--the seminal works are Henning
Bohn and Linda L. Tesar (1996) (henceforth BT) and Michael J.
Brennan and H. Henry Cao (1997) (henceforth BC)--established three
stylized facts that characterized the relationship between U.S.
international investment and returns: U.S. investors chase returns,
do not rebalance their international portfolios, and are at an
informational disadvantage when they venture abroad. These stylized
facts still inform the literature; for example, the theoretical
models in Massimo Guidolin (2005), Rui Albuquerque, Gregory H.
Bauer, and Martin Schneider (2007), and Bernard Dumas, Karen K.
Lewis, and Emilio Osambela (2010) are designed to incorporate some
of these relationships between U.S. investment and returns. The
seminal BC and BT results continue to resonate with researchers
because similar, updated bilateral flows data and similar
empirical techniques produce similar results. Using flows data,
U.S. investors still appear to chase returns and not rebalance
their international portfolios. And, consistent with an
informational disadvantage, flows into a country's equity market
are still related to the contemporaneous returns in that
market.

However, the theories in BT and BC concern portfolio
adjustments, not bilateral flows. Portfolio holdings data were not
available--such data did not exist in the 1990s--so both studies
relied on data on international capital flows. But the link from
changes in asset demands (i.e., portfolio adjustments) to bilateral
flows is not straightforward. In particular, as discussed in BC,
changes in wealth could confound such analysis. Consider a
situation in which domestic investors experience an increase in
wealth and allocate some of it to all markets (i.e., there are
positive bilateral flows to each market), but in the process reduce
the portfolio weights of some markets. If prior returns were high
in a particular market, bilateral flows-based analysis would
characterize that as returns-chasing behavior, regardless of
whether the portfolio allocation to that country increased or
decreased. BC tried to control for this by including a benchmark
domestic returns series in empirical tests, but acknowledged that
this was an imperfect fix.

Portfolio data and portfolio-based techniques, both better
suited to address the relationship between international investment
and returns, are now available. We revisit the analyses of BC and
BT using monthly estimates of bilateral portfolio positions between
the U.S. and over 40 foreign countries--data maintained by the
Federal Reserve--and the portfolio-based techniques of Mark
Grinblatt, Sheriden Titman, and Russ Wermers (1995), B. Espen Eckbo
and David C. Smith (1998), and Wayne E. Ferson and Kenneth Khang
(2002). Our results are almost completely counter to the extant
stylized facts. We do not find evidence that U.S. investors chase
returns; rather, they appear to engage in a type of partial
rebalancing by selling past winners. We do not find that U.S.
investors are necessarily at an informational disadvantage; rather,
they shift into markets just prior to their strong abnormal
returns. Taken together, our analysis suggests that foreign
equities are a very attractive asset class for U.S. investors: On
average, U.S. investors' foreign equity portfolio outperformed a
value-weighted foreign benchmark by 160 basis points per year over
the past two decades.

The paper proceeds as follows. In the next section we discuss
the seminal works and present updated flows-based results that are
consistent with their findings. In Section II we explore the
relationship between U.S. portfolios and past returns before
directly examining whether U.S. investors are at an informational
disadvantage in foreign markets. Section III compares the
performance of U.S. investors' foreign equity portfolios with
value-weighted benchmarks. In Section IV we discuss some
implications of our findings for theorists, empiricists, and
policymakers. Section V concludes.

I. The Existing Stylized Facts

The stylized facts that characterize the relationship between
U.S. international investment and returns come from the seminal BC
and BT papers, which were written at a time of limited data
availability. Recognizing the limitations, BT tested a theory of
portfolio reallocations using the then-available bilateral flows
data. Specifically, the authors test for a portfolio rebalancing
effect by examining the relationship between bilateral flows and
contemporaneous foreign returns (in excess of the rest of the
portfolio's returns). In this setup, a negative relationship
between flows and contemporaneous returns would be consistent with
portfolio rebalancing; when returns in a country were high, U.S.
investors would sell that country's equities (i.e., bilateral flows
to that country would be negative) to prevent an increased
allocation to that country. However, BT found that for many
countries the relationship is positive, indicative of a lack of
rebalancing. BT also test a returns-chasing hypothesis by examining
the relationship between bilateral flows and past (expected or
actual) returns. For many countries the relationship was positive,
indicative of returns-chasing. BC estimated similar regressions,
although in their model a positive relationship between flows and
contemporaneous returns would be evidence of an information
disadvantage; U.S. investors with poor information about a country
would purchase its equity market when its price increased. Similar
to BT, BC found a positive relationship between bilateral flows and
contemporaneous returns, indicative of poor information on the part
of U.S. investors.

BT- and BC-like regression analysis performed today, either with
data from the time periods they studied or with updated data,
produces results similar to the seminal findings. We replicate the
BT analysis using the original January 1981 to November 1994 time
period and the original 22 foreign markets (Table 1 columns 1-3).
Results from bilateral regressions of U.S. net purchases in foreign
equity market i (scaled by the lagged size of the foreign
portfolio) on expected excess returns in market i (returns
in excess of a one-month eurodollar rate) are in column 1. As in
BT, excess returns are forecasted using an information set
consisting of lagged values of the following: world returns, U.S.
excess dividend yield, U.S. term structure, and the foreign
country's excess return and dividend yield. In the BT's reported
baseline results, 7 (or 11, depending on the scale factor for
flows) out of 22 coefficients on expected returns were positive and
significant. In our replication exercise, 7 of 22 coefficients are
positive and significant. In column (4)
we re-estimate using updated data from January 1990 to December
2008; results are similar, with 8 of the 22 coefficients on
expected returns positive and significant. For contemporaneous
returns updated data produce even stronger results; the correlation
between bilateral flows and contemporaneous returns (0) is positive and significant for 10 countries over the
BT period and for 15 countries in the updated sample (columns 2 and
5). Finally, the correlation between flows and lagged returns
(1) is positive and significant for 6
countries using the old sample, 13 in the updated samples (columns
3 and 6). The stylized facts continue to inform the literature in
part because similar flows-based data and techniques would lead to
similar conclusions today (see, for example, Albuquerque, Bauer,
and Schneider 2009).

II. A Reassessment of Returns Chasing and Informational
Disadvantages in U.S. International Equity Portfolios

The theories in BT and BC are fundamentally about changes in
asset demands. The mapping from changes in asset demands to
bilateral flows is straightforward if wealth is constant. But
financial wealth is not constant (Figure 1). A more direct test of
the theories requires data on portfolio allocations. We describe
such data next, and then employ portfolio-based techniques to
re-examine the relationship between international investment and
past and prospective returns.

A. The Portfolio Data

A portfolio-based study of U.S. investors' trading style is made
possible by the Carol C. Bertaut and Ralph W. Tryon (2007)
estimates of the monthly bilateral positions of U.S. investors in
the equities of a large set of foreign countries. The country-level
dataset includes, for example, a monthly time series of U.S.
holdings of German equities (as well the U.S. holdings of equities
in many other foreign countries).

Bertaut and Tryon (2007) form the data by combining high-quality
low frequency readings on positions, built from security-level
benchmark surveys, with higher frequency (monthly) flow data. In
the process of combining positions and flows data, the reported
flow data is adjusted to alleviate the well-known financial center
bias; in the reported flow data, because of the U.S. government's
data collection methodology far too many flows are attributed to
financial centers like the United Kingdom (see, among others
Warnock and Chad Cleaver 2003). Specifically, Bertaut and Tryon
(2007) form monthly bilateral positions by starting with an initial
position as given by a benchmark survey, forming naïve monthly
positions until the next benchmark survey by using flow data and
valuation adjustments (from, for foreign equity markets, MSCI
indexes), and then adjusting the estimates to eliminate the
financial center bias and other wedges between flows-based
estimates and survey-based readings.1

The resulting dataset is entirely consistent with officially
reported data on U.S. holdings of foreign equities published in
U.S. Treasury's annual benchmark surveys and in BEA's U.S.
international investment position presentation, as well as with
data in both the Philip R. Lane and Gian Maria Milesi-Ferretti
(2007) dataset and the IMF's Coordinated Portfolio Investment
Survey (CPIS). In fact, an earlier version of the Bertaut Tryon
dataset formed the basis for the official U.S. entries in the CPIS
for 2002, a year in which the United States did not conduct a
benchmark asset survey.2 Aggregate Bertaut and Tryon (2007)
data--that is, aggregate foreign positions in U.S. securities and
aggregate (not bilateral) U.S. positions in foreign
securities--have been used in Curcuru, Tomas Dvorak, and Warnock
(2008, 2010) and Curcuru, Thomas, and Warnock (2009) to show that
(i) previous estimates of the differential between returns on U.S.
investors' foreign portfolios and returns on foreigners' U.S.
positions were biased upward and (ii) foreigners' U.S. portfolio
returns were reduced by ill-timed switching between U.S. bonds and
U.S. equities, whereas U.S. investors' foreign returns were not
degraded by switching between asset classes.

The bilateral holdings data provide the country weights in U.S.
investors' portfolios. Armed with these weights, and assuming that
within each country the market (as represented by MSCI firms) is
held, the (unhedged) dollar returns earned by U.S. investors on
their foreign equity portfolios can be computed.

B. The Relationship Between Portfolio Reallocations and Past
Returns

Portfolio weights and returns enable an examination of the
relationship between portfolio reallocations and past returns using
well-established portfolio-based techniques. To test for momentum
and portfolio rebalancing, we use the Grinblatt, Titman, and
Wermers (1995) momentum statistics to measure the degree to which
U.S. investors actively change their portfolio holdings in the
direction of previous country-level stock returns. The statistics
are computed as follows. Specifically, define Xi,t as the
active change in the weight of country i in U.S. investors'
foreign portfolio at time t:

(1)

where ri,,t is the return on country i equities
from period t-1 to t; rp,t is the return on
U.S. investors' foreign portfolio, defined as
; and
wi,t is the weight of country i at time t in
U.S. investors' portfolio. If investors follow a buy-and-hold
strategy, Xi,t would equal zero. There are three momentum
measures:

(2)

(3)

(4)

where Nt is the number of countries held in the portfolio
at time t and k is the number of periods the returns
are lagged. A significant, positive LM measure indicates a momentum
trading strategy: U.S. investors on average increased the weights
on countries whose equities performed well (relative to the other
markets) k periods ago. A significantly negative value of LM
would be evidence of contrarian trading, which is consistent with a
portfolio balancing effect. The two additional momentum statistics
isolate trading when investors increase country weights (the BM
measure) from when they decrease country weights (the SM
measure).

The results are in Table 2. The LM measure is sometimes
positive, sometimes negative, but never statistically significant,
indicating that when U.S. investors venture abroad, their trading
strategy can be characterized as neither momentum following nor
contrarian. The BM and SM lines show results when we split the
sample into instances in which U.S. investors increased the
portfolio weight on country i (BM Buy Only) and instances
when they decreased the weight on country i (SM Sell Only).
There is again very little evidence of momentum trading; the
coefficients on the BM statistic are usually (but not always)
positive, indicating that U.S. investors moved into markets that
recently performed well, but the statistic is significant in only
two of nine cases. In contrast, there is strong evidence that U.S.
investors can be characterized as contrarian when selling; the SM
(Sell Only) coefficient is negative for all samples and lags,
significantly so in eight of nine cases. In their international
equity portfolios U.S. investors sell past winners--consistent with
a partial portfolio rebalancing effect--and this behavior is
apparent in both developed and emerging markets.3,4

C. The Relationship between Portfolio Reallocations and Future Returns

The conditional weight-based measure (CWM)--a portfolio-based
measure developed by Grinblatt and Titman (1993), Eckbo and Smith
(1998), and Ferson and Khang (2002) that is based on an estimate of
the sum of the covariances between changes in portfolio weights and
future abnormal returns--is a direct measure of the relationship
between portfolio reallocations and prospective returns. The CWM is
used in the literature as a gauge of private information or an
informational advantage. Under time-varying expected returns, a
risk-averse investor with non-increasing absolute risk aversion
would move into (out of) a market when private information
indicates a positive (negative) abnormal return relative to that
predicted using public information, and in this case the estimate
of the sum of the conditional covariances between changes in
portfolio weight and future abnormal returns would be positive.

CWM is set up as follows. Define the estimate of the sum of the
conditional covariances as

(5)

where
is the benchmark weight of
country i at time t. Let the benchmark be a
buy-and-hold weight of lag k defined as

(6)

Estimate the conditional portfolio weight-based measure via
GMM:

(7)

(8)

Equation (7) is an N vector of
errors from estimating a linear function of future excess returns
on information variables when N is the maximum value of
Nt for the full sample. Zt, a subset of
, arepublic
information variables. We use three variables to proxy for public
information: lagged changes in the short-term interest rate (U.S.
Treasury three-month yield); lagged changes in term structure
spread (U.S. Treasury 10-year yield minus U.S. Treasury 3-month
yield); and lagged world excess returns.5 Each error in equation
(7) can be interpreted as an abnormal
return. Equation (8) is the error from
estimating an average of the conditional covariances between
changes in portfolio weights and future abnormal returns.
p is the average conditional weight
measure across the full sample. We set up the following system of
moment conditions

(9)

The vector of sample moment conditions g is a NL+L
vector, where L is the number of information variables, and the
parameters are N vectors of L by 1 (bi) and the scalar
p . Because the starting date in our
dataset varies by country, we follow Ravi Bansal and Magnus
Dahlquist (2000) and define an indicator variable Ii,t that
denotes data availability for a country i at time t.
As long as Ii,t is independent of the error terms from
equations (7) and (8)--for example, missing data are not all in
periods with abnormally high excess returns--the indicator variable
can be used to in effect fill in missing values with zeros. The
augmented set of moments conditions is

(10)

Table 3 shows estimates of the average conditional portfolio
weight measure, p, estimated from the system
of equations (7) and (8) against one-, two-, and three-month benchmark
buy-and-hold strategies (k=1, 2, 3, respectively). In the
All Foreign Countries sample and for Advanced Economies, the CWM
statistic is positive and significant for all lags. U.S. investors
realize positive excess returns over a strategy that prohibits
trading within their foreign portfolios for one, two or three
months; that is, they reallocate into markets just prior to
positive abnormal returns. For emerging markets, the evidence is
less compelling; CWM statistic is positive and large in magnitude,
but is statistically significant only for k=2.

The positive and significant estimate of the sum of the
conditional covariances between changes in portfolio weights (for
the full sample and Advanced Economies) and future abnormal returns
can be interpreted as evidence of trading expertise from private
information. Overall, the main conclusion from the CWM analysis is
that U.S. investors switch into markets prior to abnormally strong
returns, although the evidence from their emerging market
portfolios is somewhat weaker.

D. What Drives the Results: Data or Techniques?

Relative to the seminal papers, our analysis differs along two
dimensions. First, our data differ not only because they are
portfolio reallocations (consistent with theory) but also because
they correct a severe financial center bias in the as-reported
bilateral flows data (Warnock and Cleaver 2003). Second, the
portfolio data enable the use of alternative portfolio-based
techniques; the main difference there is that each country is
examined in conjunction with the rest of the portfolio, not in
isolation as in bilateral flows-based analysis.

To determine what is driving our results, we rerun our analysis
retaining the original country-by-country techniques but using two
alternative sets of data. First, we use "restated" bilateral
flows. Restated flows are not as-reported, but rather are
consistent with the Bertaut and Tryon (2007) dataset in that the
financial center bias has been eliminated. Original empirical
techniques using restated bilateral flows (as opposed to
TIC-reported bilateral flows) produce results very similar to, if
not stronger than, the results in the seminal papers (Table 4,
columns 1-3). Correcting for financial center biases does not yield
results that differ from the old stylized facts. Next, we conduct
the same bilateral analysis but using portfolio reallocations (our
X variable from equation 1). Doing so results in many fewer
positive and significant estimates (columns 4-6).

Relative to the seminal results, our results appear to be driven
by the use of portfolio reallocations instead of flows. This, in
turn, suggests that the main problem with flows data is that they
do not account for changes in the size of (and reallocations
within) U.S. portfolios. Indeed, the correlation between flows and
portfolio reallocations is quite low. If the mapping from portfolio
reallocations to flows were perfect, the correlation would be one.
But across the 43 markets in our study, the correlation averages
0.28 and is less than 0.5 for all but five countries. There is a
link from portfolio reallocations to flows, but it is not
straightforward in theory and is not tight in the data.

III. Unconditional Portfolio Performance

Results from the 1990s suggested that U.S. investors' foreign
portfolios earned less than the value-weighted benchmark; see, for
example, evidence in BT. In contrast, updated data indicates that
in almost every year since 1990 U.S. investors' foreign portfolio
beat a value-weighted benchmark, constructed using MSCI market
capitalization weights for the 43 countries in our sample (Figure
2). The higher mean returns did not come at the expense of higher
volatility. Compared to the value-weighted foreign portfolio, U.S.
investors' foreign equity portfolio earned higher returns (0.21
percent monthly excess returns vs. 0.08 for the value-weighted
portfolio) with less volatility (4.7 vs. 4.9) for a significantly
higher Sharpe ratio (Table 5). Relative performance within the set
of developed countries is similar, with U.S. investors' portfolios
earning higher returns with less volatility, producing a
significantly greater Sharpe ratio (4.1 vs. 1.3). In emerging
markets, U.S. investors earned higher returns (0.82 percent per
month vs. 0.71 percent) but with slightly higher volatility (7.5
vs. 7.2). The unconditional performance of U.S. investors'
international equity portfolios has been quite good.

IV. Implications

An obvious implication of our results is that theoretical models
of international portfolio choice should not be explicitly designed
to produce returns-chasing behavior, as some have in the past
(Guidolin, 2005; Albuquerque, Bauer, and Schneider 2007).
Returns-chasing can arise naturally from a rich model, such as in
Victoria Hnatkovska (2010), but theorists should hesitate before
treating returns-chasing as a stylized fact a model should be
designed to produce.6

Somewhat more subtle but perhaps equally important is that
theoretical international macro models that incorporate
international portfolio choice, which have recently become more
prevalent (e.g., Cedric Tille and Eric van Wincoop 2008, 2010;
Michael B. Devereux and Alan Sutherland 2010, forthcoming;
Hnatkovska 2010), must take seriously the fact that fluctuations in
financial wealth are important. Tille and van Wincoop (2010) stress
the role of portfolio growth, but, following Aart Kraay and Jaume
Ventura (2000, 2003), portfolio growth in their model is
essentially net national savings (net capital flows). Just as the
empirical capital flows literature has begun to focus on gross
instead of net flows (Fernando A. Broner et al 2010; Kristin J.
Forbes and Warnock 2010), theorists must recognize that substantial
variations in financial wealth can confound some of the facts
around which models are being built.

Our analysis also suggests that empiricists should refrain from
attaching labels like herding behavior and returns-chasing when the
basis for the analysis is flows data. For example, Ken Miyajima and
Huanhuan Zheng (2010), part of the IMF's October 2010 Global
Financial Stability Report, examines the relationship between
(proprietary) bilateral flows and returns, and reports that
investors chase returns and exhibit herding. We find the exact
opposite results using portfolio data. In our view, if the concept
concerns portfolio adjustments, portfolio rather than flows data
should be employed.7

Many empirical studies have found that foreigners perform poorly
when investing in countries ranging from Indonesia (Dvorak, 2005)
and Korea (Hyuk Choe, Bong-Chan Kho, and Stulz, 2005) to Germany
(Harald Hau, 2001), so our finding that U.S. investors reallocate
into markets just prior to strong returns might appear puzzling.
However, recall that our analysis concerns country picking, not
within-country timing and execution. Moreover, our results are not
inconsistent with empirical work on the predictability of equity
prices, especially for one market relative to another. Ferson and
Harvey (1993) find some predictability of international equity
returns, Kenneth Kasa (1992) finds mean reversion (and, hence, some
predictability) in two-country equity portfolios, and Anthony J.
Richards (1995) and Ronald Balvers, Yangru Wu, and Erik Gilliland
(2000) find that country-specific returns relative to a world index
exhibit mean reversion, suggesting that the contrarian strategy of
Werner F. M. DeBondt and Richard H. Thaler (1985) and Richards
(1997) might be profitable. Thus, both partial rebalancing--the
selling of equity markets that performed well in the recent
past--and switching into markets that subsequently have high
abnormal returns are consistent with the literature on the
predictability of international equity market returns. While it may
well be difficult for a foreigner to time a market, some skill at
timing reallocations between markets is plausible and consistent
with both theory and our results.

V. Conclusion

Many of the stylized facts regarding U.S. investment abroad came
out of an era when appropriate data were not available. Many of the
seminal results relied on bilateral capital flows data, when the
theories called for data on portfolio reallocations. Theory had
progressed enough so that researchers knew what relationships
should be examined, but appropriate data did not exist. A
limitation of flows-based analysis is that it can be confounded by
wealth effects. Portfolio-based techniques are consistent with
theories of international portfolio choice and are not subject to
this limitation.

Using portfolio-based data and techniques, we find evidence that
contradicts long-standing stylized facts. U.S. investors do not
chase past returns, nor do they refrain from rebalancing their
international portfolios. Rather, they sell past winners, a form of
partial rebalancing. U.S. investors do not appear to be at an
informational disadvantage when they venture abroad. Rather,
consistent with having superior information, there is a positive
relationship between portfolio reallocations and future returns;
U.S. investors increase portfolio weights on a country's equity
market just prior to its strong performance. Our results indicate
that U.S. investors beat the value-weighted foreign benchmark by an
average of 162 basis points per year from 1990-2008.

Our analysis suggests researchers and policymakers should be
cautious when using flow data to examine portfolio behavior. Best
is to use portfolio data. In cases in which flows data must be
used, controlling for changes in wealth is vital.

For expected returns, b1 coefficients are from bilateral
regressions of the form
, where NPi,t is reported U.S. net purchases of country
i equities, Wt-1 is the lagged foreign portfolio, and
is the expected
returns (in excess of a one-month T-bill rate) in market i
forecasted using lagged information variables (world return, U.S.
excess dividend yield, U.S. term structure, and country i's
excess return and dividend yield). Correlations between net
purchases and contemporaneous and lagged returns denoted by
0 and 1, respectively.
Monthly data over 1981-1994 and 1990-2008. ** and * denote
statistical significance at the 5 and 10 percent levels,
respectively.

where ri,t+1 is the vector of portfolio excess returns in
month t+1 , bi is the matrix of coefficients from regressing
ri,t+1 on the instruments, Zt (including a constant),
and the parameter p is the average
conditional covariance.Newey and West (1987) standard errors are in
parentheses.
** and * denote statistical significance at the 5 and 10 percent levels, respectively.

Table 4: Restated Flows, Reallocations, and Returns

Restated Flows: b1 (1)

Restated Flows: 0 (2)

Restated Flows: 1 (3)

Portfolio Reallocations: b1 (4)

Portfolio Reallocations: 0(5)

Portfolio Reallocations: 1 (6)

Australia

0.44*

0.21**

0.27**

-0.12

0.21

-0.89

Austria

0.02

0.15**

0.19**

0.01

0.02

-0.02

Belgium

-0.20

-0.38

-0.10

-0.32

-0.72

0.34**

Canada

1.11**

0.30**

0.22**

1.01*

0.23

0.27

Denmark

0.00

-0.04

0.00

-0.11

0.11

-0.15

Finland

0.17**

0.29**

0.18**

0.11

0.09

-0.16

France

1.34

-0.04

0.00

-2.37

-5.07

0.21

Germany

0.90

0.18**

0.15**

5.01**

10.51**

-0.11

Hong Kong

0.17

0.14**

-0.03

0.13

0.10

-0.15

Ireland

-0.04

-0.23

-0.12

-0.18

-0.18

-0.06

Italy

-0.27

0.13**

0.06

-0.48

-0.01

-0.30

Japan

1.36

0.38**

0.33**

0.16

1.09

-0.64

Netherlands

1.54**

-0.01

-0.05

-0.27

2.23**

-0.76

Norway

0.08*

0.18**

0.16**

0.05

0.00

0.02

Singapore

0.03

0.11

0.16**

0.03

0.03

0.00

Spain

-0.07

0.13*

-0.01

-0.35

-0.15

0.12

Sweden

0.53*

0.11*

0.13*

0.20

0.34

0.03

Switzerland

0.30

0.00

0.01

-1.84

-1.57

0.66

UK

3.05

-0.01

0.01

-2.09

-0.60

-0.14

Mexico

1.13**

0.22**

0.14**

0.84**

1.40**

-0.12

Malaysia

0.10**

0.21**

0.19**

0.11**

0.03

0.02

South Africa

0.12**

0.19**

0.15**

-0.03

-0.05

0.00

The relationship between restated TIC flows (restated U.S. net
purchases of country i equities as a share of the lagged
foreign portfolio) or, alternatively, active portfolio
reallocations (our Xi,t variable) and expected,
contemporaneous, and lagged returns. Definitions for b1 ,
0, and 1 are in Table 1.
Data are monthly from January 1990 to December 2008. ** and
* denote statistical significance at the 5 and 10 percent levels,
respectively.

Means, standard deviations, and Sharpe ratios (mean divided by
standard deviation) for portfolios of foreign equities. Returns are
in excess of a one-month Eurodollar interest rate and are expressed
in monthly percentage points. Value-weighted benchmarks are
portfolios based on MSCI market capitalization weights. U.S.
investors' portfolios are based on U.S. investors' holdings.
The Chi-squared: Sharpe Ratio is a test statistic for the
null hypothesis that Sharpe ratios in the two columns are equal.
Sample period is January 1990 through December 2008. Asymptotic
p-values computed from Newey and West (1987) standard errors
are in brackets. * Statistically significant at the 10
percent level.

Figure 1: U.S. Financial Wealth

Total financial assets of households and nonprofit organizations
(line L.100 from the Federal Reserve's Flow of Funds dataset) in
trillions of U.S. dollars from 1985 to 2009.

Data for Figure 1

Year

Trillions of U.S. Dollars

1985

9951.8

1986

11069.8

1987

11726.1

1988

12859.1

1989

14184.4

1990

14549.5

1991

16106

1992

16950.2

1993

18226.4

1994

18902.1

1995

21502.6

1996

23398.4

1997

26707.9

1998

30041.4

1999

34479.5

2000

33350.6

2001

32210.1

2002

30236.3

2003

35336.1

2004

39217.5

2005

43306.2

2006

48089

2007

50662.8

2008

41431.4

2009

44260.2

Figure 2: Comparison of Portfolio Returns

Annual returns (in excess of a one-month Eurodollar interest
rate) for a benchmark portfolio based on MSCI market capitalization
weights (Value-Weighted) and a portfolio based on U.S.
investors' holdings (U.S. Investors).

Data for Figure 2

Year

Value-Weighted

US Investors

1990

-30.14490675

-19.54040449

1991

8.61841105

11.87509998

1992

-14.23542697

-9.630033626

1993

28.89716485

29.23032376

1994

4.033962302

-2.101346998

1995

3.517481471

6.982062278

1996

1.782342768

7.327249932

1997

-2.030812391

3.364128188

1998

10.60645993

11.53475594

1999

23.70595542

23.51960089

2000

-21.40721564

-19.06469928

2001

-23.61155109

-22.8767787

2002

-15.77587591

-16.64332505

2003

34.99258847

35.01601597

2004

18.71897443

18.8936716

2005

13.45089691

14.62528952

2006

20.10373725

20.54082515

2007

12.96515922

13.17032026

2008

-56.2641253

-57.46245609

Footnotes

** Curcuru: Board of Governors of the Federal Reserve System,
Washington DC 20551, stephanie.e.curcuru@frb.gov. Thomas: Board of
Governors of the Federal Reserve System, Washington DC 20551,
charles.thomas@frb.gov. Warnock: Darden Business School, University
of Virginia, Charlottesville, VA 22906-6550, and National Bureau of
Economic Research, warnockf@darden.virginia.edu. Wongswan: Phatra
Securities Public Company Limited, Bangkok 10310 Thailand,
jon@phatrasecurities.com. We thank the referees, Galina Hale, Assaf
Razin, Giorgio Valente, and participants in seminars and
conferences including BIS, Clemson University, De Nederlandsche
Bank, ECB-JIE, Federal Reserve Bank of Dallas, Federal Reserve
Board, Georgetown University, Hong Kong Monetary Authority,
Universiteit van Amsterdam, University of Oregon, and University of
Virginia. James Albertus provided excellent research assistance.
Warnock thanks the Darden School Foundation for generous support
and the Asian Institute of Management for its hospitality. Also
released as NBER Working Paper 16677. The views in this paper are
solely the responsibility of the authors and should not be
interpreted as reflecting the views of the Federal Reserve Bank of
Dallas, the Board of Governors of the Federal Reserve System, or of
any other person associated with the Federal Reserve System. Return to text

1. Bertaut and Tryon (2007) includes a
detailed discussion of the methodology. Return to text

2. While the Bertaut and Tryon (2007)
dataset is the best currently available for monthly U.S. investment
in foreign equities, in the future such data could be improved in
two ways. First, more frequent measurements of positions might
become available; the less time between measurements of positions,
the more accurate are the interim estimates. In recent years, the
surveys have been annual, but in mid-2011 collection of monthly
data on aggregate positions by country will commence, which could
improve the accuracy of interim holdings estimates. Second, monthly
estimates could become more accurate by incorporating more direct
measures of the returns U.S. investors earn in foreign markets. No
such returns series currently exist, but someone covered under the
International Investment Act of 1987 could, in theory, construct
them. For now, we must rely on publicly available returns indices.
Fortunately, within countries, MSCI indices seem to be
representative of U.S. investment; MSCI firms represent almost 80
percent of U.S. investors' foreign equity investment, and an
examination of U.S. holdings in over 12,000 foreign firms as of a
point in time (December 1997) showed that the correlation between
weights in the MSCI World Ex US Index and U.S. investors' foreign
equity portfolios is quite high at 0.77 (John Ammer et al.
2006). Return to text

3. At first glance, our contrarian when
selling results appear to contrast with Graciela Kaminsky, Richard
K. Lyons, and Sergio L. Schmukler (2004), who find that 13 Latin
American mutual funds exhibit momentum trading over the period from
1993 - 1999. However, most of their evidence pertains to LM (Buy
and Sell) at a zero lag; we do not analyze contemporaneous momentum
statistics because it is impossible to disentangle true momentum
trading (reallocations following price changes) from price pressure
(price reacting to reallocations). Moreover, Kaminsky, Lyons, and
Schmukler (2004) do not compute BM and SM statistics, so our
studies are not directly comparable. Return to text

4. One caveat about time series data on
portfolios is that they include stock swaps that arise from
international mergers and acquisitions and can induce jumps in Xi,t
that are not related to trading (William L. Griever, Gary A. Lee,
and Warnock 2001). There is no ideal way to deal with stock swaps,
so we reestimated (2), (3), and (4) omitting acquisitions via stock
swaps. Excluding stock swaps, the overall LM statistic remains
insignificant in all cases, BM is positive and significant in 4 out
of 9 cases, and in 7 of 9 cases the SM statistic is negative and
significant. Excluding stock swaps, the weight of evidence still
indicates that U.S. investors sell past winners. Return to text

5. These information variables have been
found to have robust predictive power for aggregate country-level
returns (Campbell R. Harvey, 1991; Ferson and Harvey, 1993; and
Geert Bekaert and Harvey, 1997). We also experimented with lagged
local excess returns, but found that including this variable does
not change our results. We do not use the local or global dividend
yield. Ferson, Sergei Sarkisssian, and Timothy T. Simin (2003)
illustrate that returns prediction regressions with persistent
variables such as the dividend yield tend to over-reject the null
hypothesis of no predictability. Moreover, John Y. Campbell and
Motohiro Yogo (2006), who account for this bias in a study of the
U.S. market, and Andrew Ang and Bekaert (2007) and Bekaert, Harvey,
and Christian Lundblad (2007), who use Monte Carlo simulations for
a range of emerging and developed markets, find no predictive power
for the dividend yield. Return to
text

6. Even in models rich enough to deliver a
clear prediction about the relationship between flows and returns
(e.g., Dumas, Lewis, and Osambela 2010), focusing on changes in
portfolio weights rather than flows might be more
appropriate. Return to text

7. To be exact, our results concern the
foreign portfolio. It is plausible that returns-chasing could be
absent in the foreign portfolio but present in the global
portfolio, which includes domestic holdings. However, there is also
no evidence of returns-chasing in U.S. investors' global equity
portfolios (Curcuru et al. 2010). Return
to text